def run(dlcs, SAVE=None):
wsp = 18
C1 = IPC04.make()
C2 = IPC07.make()
P = BladeModel.Blade(wsp)
sys1 = ControlDesign.Turbine(P, C1)
sys2 = ControlDesign.Turbine(P, C2)
#ControllerEvaluation.plot_nyquist(sys.L, zoom=1.5, rightticks = True, save=SAVE)
plot_T(sys1.T, sys2.T, SAVE=SAVE)
def run(dlc=None, dlc_noipc=None, SAVE=None):
f = np.linspace(0, 1.5, 1000)[1:]
Yol = OLResponse.Response(18)
Ycl = Spectrum(dlc(wsp=18, controller='ipcpi')[0])
C = make()
P = BladeModel.Blade(18)
sys = ControlDesign.Turbine(P, C)
mag = signal.bode(sys.S, w=f * (2 * np.pi))[1]
actualMag = 20 * np.log10(Ycl(f) / Yol(f))
fig, ax = ControllerEvaluation.magplotSetup(F1p=0.16)
ax.set_xlim(0.05, 1.5)
ax.axhline(0, lw=1, c='0.8', ls='-')
ax.plot(f, mag, label='$S(C_{PI})$, linear model')
ax.plot(f, actualMag, '--', label='$S(C_{PI})$, HAWC2 model')
ax.set_ylim(-10, 10)
ax.legend(loc='upper left')
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
def run(dlc=None, dlc_noipc=None, SAVE=None):
wsp = 18
C = make()
P = BladeModel.Blade(wsp)
sys = ControlDesign.Turbine(P, C)
plot_nyquist(sys.L, zoom=1.5, rightticks = True, save=SAVE)
def run(dlc=None, dlc_noipc=None, SAVE=None):
f = np.linspace(0, 1.5, 1000)[1:]
C = []
modules = ['IPC_PI', 'IPC04', 'IPC07']
for m in modules:
module = importlib.import_module('Controllers.' + m)
C.append(module.make)
Mag = []
for c in C:
P = BladeModel.Blade(18)
sys = ControlDesign.Turbine(P, c())
Mag.append(signal.bode(sys.S, w=f * (2 * np.pi))[1])
fig, ax = ControllerEvaluation.magplotSetup(F1p=0.16)
ax.set_xlim(0.05, 1.5)
ax.plot(f, Mag[0], '-.', label='$S(C_{PI})$')
ax.plot(f, Mag[1], ':', label='$S(C_{1p})$')
ax.plot(f, Mag[2], '-r', label='$S(C_{2})$')
ax.set_ylim(-25, 10)
ax.legend()
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
def run(dlc=None, dlc_noipc=None, SAVE=None):
f = np.linspace(0, 1.5, 1000)[1:]
C = []
modules = ['IPC_PI', 'IPC04', 'IPC09', 'IPC10', 'IPC11']
for m in modules:
module = importlib.import_module('Controllers.' + m)
C.append(module.make)
Mag = []
for i in [0, 1, 2, 3, 4]:
P = BladeModel.Blade(18)
sys = ControlDesign.Turbine(P, C[i]())
Mag.append(signal.bode(sys.S, w=f * (2 * np.pi))[1])
fig, ax = ControllerEvaluation.magplotSetup(F1p=0.16)
ax.set_xlim(0.05, 1.5)
ax.axhline(0, lw=1, c='0.8', ls='-')
colors = ['#a1dab4', '#41b6c4', '#2c7fb8', '#253494']
ax.plot(f, Mag[0], '-.', c='tab:orange', label='$S(C_{PI})$')
for i in [1, 2, 3, 4]:
ax.plot(f,
Mag[i],
'-',
c=colors[i - 1],
label='$S(C_{f' + f'{i}' + 'p})$')
ax.set_ylim(-25, 10)
ax.legend()
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
def run(dlc=None, dlc_noipc=None, SAVE=None):
wsp = 18
# Load transfer functions
C = make()
P = BladeModel.Blade(wsp)
Kps, Tis = np.meshgrid([0.01, 0.015, 0.02], [0.5, 1, 2])
fig, axes = plt.subplots(3, 3, sharex=False, sharey=False, figsize=(7, 7))
plt.subplots_adjust(wspace=0.05, hspace=0.05)
for i in range(3):
for j in range(3):
C = make(Kp=Kps[i, j], Ti=Tis[i, j])
sys = ControlDesign.Turbine(P, C)
plot_nyquist(sys.L, axes=axes[i, j], zoom=1, margin=True)
perf = sys.performance(0.16)[0]
axes[i, j].text(0,
0,
'$f_{1p}$: ' + '{:2.2f}\%'.format(perf * 100),
transform=axes[i, j].transAxes,
va='bottom')
fig.text(0.1, 0.5, 'Real', va='center', rotation='vertical')
fig.text(0.5, 0.1, 'Imaginary', ha='center', rotation='horizontal')
for i in range(3):
axes[0, i].set_title(f'$K_p=${Kps[0, i]}')
axes[i, 2].yaxis.set_label_position('right')
axes[i, 2].set_ylabel(f'$T_i=${Tis[i, 0]}')
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
def getData():
f1p = 0.16
fs = f1p * np.array([1, 2, 3, 4])
X = []
P = BladeModel.Blade(wsp=18)
Yol = OLResponse.Response(18)
# loop over each controller
for i, mod_name in enumerate(Modules):
X.append({})
# load linear closed loop system
module = import_module('Controllers.' + mod_name)
C = module.make()
sys = ControlDesign.Turbine(P, C)
X[i]['sm'] = sys.sm
X[i]['linear'] = list(sys.performance(f1p))
# load HAWC2 closed loop system results
dlc = PostProc.DLC('dlc11_1')
Sim = dlc(wsp=18, controller=ControllerName[i])[0]
Ycl = Spectrum(Sim)
X[i]['HAWC2'] = [Ycl(f) / Yol(f) - 1 for f in fs]
return X
def run(dlc, dlc_noipc, c, C, SAVE=False):
WSP = [6, 12, 18, 24]
fnp = 0.16 * np.array([1, 2, 3, 4])
for wsp in WSP:
# Load transfer functions
P = BladeModel.Blade(wsp)
Yol = OLResponse.Response(wsp)
# Calculate predicted output spectrum
system = ControlDesign.Turbine(P, C)
w, H = signal.freqresp(system.S)
f = w / (2 * np.pi)
Ycl_pred = abs(H) * Yol(f)
# Load close loop output spectrum
Sim = dlc(yaw=0, wsp=wsp, controller=c, Kp=-1)[0]
Ycl = Spectrum(Sim)
fig, ax = magplotSetup(F1p=0.16)
ax.set_ylabel('Magnitude [m]')
ax.plot(f, Yol(f), label='$Y_{OL}$')
ax.plot(f, Ycl_pred, '--k', label='$Y_{CL}$ (predicted)')
ax.plot(f, Ycl(f), 'r', label='$Y_{CL}$ (actual)')
ax.set_xlim(f.min(), 1.5)
ax.set_title('wsp = {}m/s'.format(wsp))
ax.legend()
if SAVE:
plt.savefig(
'../Figures/{}/{}_TipDeflection_Spectrum_{}.png'.format(
c, c, wsp),
dpi=200)
plt.show()
print()
for f in fnp:
pred = abs(signal.freqresp(system.S,
f * 2 * np.pi)[1][0]) * 100 - 100
act = Ycl(f) / Yol(f) * 100 - 100
print('{:2.2f}%, {:2.2f}%'.format(pred, act))
def run(dlc=None, dlc_noipc=None, SAVE=None):
f = np.linspace(0, 1.5, 1000)[1:]
Yol = OLResponse.Response(18)
Ycl = Spectrum(dlc(wsp=18, controller='ipcpi')[0])
C = make()
P = BladeModel.Blade(18)
sys = ControlDesign.Turbine(P, C)
mag = signal.bode(sys.S, w=f * (2 * np.pi))[1]
#actualMag = 20*np.log10(Ycl(f)/Yol(f))
w, H = signal.freqresp(sys.S, n=100000)
f = w / (2 * np.pi)
Ycl_pred = abs(H) * Yol(f)
fig, ax = ControllerEvaluation.magplotSetup(F1p=0.16)
ax.set_xlim(0.05, 1.5)
ax.axhline(0, lw=1, c='0.8', ls='-')
ax.plot(f, Yol(f), label='Open loop')
ax.plot(f, Ycl_pred, '--k', label='Closed loop (linear)')
ax.plot(f, Ycl(f), 'r', label='Closed loop (HAWC2)')
#ax.plot(f, mag, label='$S(C_{PI})$, linear model')
#ax.plot(f, actualMag, '--', label='$S(C_{PI})$, HAWC2 model')
ax.set_ylabel('Magnitude [m]')
ax.set_xlim(0.05, 1.5)
ax.set_ylim(0.01, 0.4)
ax.set_yscale('log')
ax.legend(loc='upper right')
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
controller.addLeadCompensator(lead, 3*F1P)
controller.addLeadCompensator(lead, 3*F1P)
mag, phase = controller.freqResp(2*F1P)
controller.K = 1/mag
controller.K *= 0.05
return controller.tf
if __name__ == '__main__':
wsp = 18
f1p = 0.16 # hz
P = BladeModel.Blade(wsp)
C = make()
sys = ControlDesign.Turbine(P, C)
# stability margin
print('Sm: {:2.3f}\n'.format(sys.sm))
# performance at f1p to f4p
for i, perf in enumerate(sys.performance(f1p)):
print('f{}p: {:+.2f}%'.format(i+1, perf*100))
def run(dlc, dlc_noipc, SAVE=False):
F1p = 0.16
wsp = 18
C_names = ['ipc04', 'ipc09', 'ipc10', 'ipc11']
C_labels = [
'$f_{1p}$ Control', '$f_{2p}$ Control', '$f_{3p}$ Control',
'$f_{4p}$ Control'
]
C_generators = [IPC04.make, IPC09.make, IPC10.make, IPC11.make]
fig, axes = plt.subplots(2, 2, sharey=True, figsize=[7, 5])
plt.subplots_adjust(wspace=0.05, hspace=0.05)
for c, c_func, ax, label in zip(C_names, C_generators, axes.ravel(),
C_labels):
# Load transfer functions
C = c_func()
P = BladeModel.Blade(wsp)
Yol = OLResponse.Response(wsp)
# Calculate predicted output spectrum
system = ControlDesign.Turbine(P, C)
w, H = signal.freqresp(system.S)
f = w / (2 * np.pi)
Ycl_pred = abs(H) * Yol(f)
# Load close loop output spectrum
Sim = dlc(yaw=0, wsp=wsp, controller=c, Kp=-1)[0]
Ycl = Spectrum(Sim)
ax.plot(f, Yol(f), label='OL')
ax.plot(f, Ycl_pred, '--k', label='CL (linear)')
ax.plot(f, Ycl(f), 'r', label='CL (HAWC2)')
# axis
ax.set_xscale('log')
ax.set_xlim(0.05, 1.5)
ax.set_ylim(0.01, 1)
# ticks
ax.set_xticks([F1p, 2 * F1p, 3 * F1p, 4 * F1p], minor=True)
ax.grid(axis='x', which='minor')
# annotate
ax.annotate(label,
xy=(0.05, 0.96),
xycoords='axes fraction',
size=12,
ha='left',
va='top',
bbox=dict(boxstyle='round', fc='w', alpha=0.0))
# axis
ax.set_yscale('log')
ax.set_ylim(0.01, 1)
# ticks
axes[0, 0].set_xticklabels([])
axes[0, 1].set_xticklabels([])
axes[1,
0].set_xticklabels(['$f_{1p}$', '$f_{2p}$', '$f_{3p}$', '$f_{4p}$'],
minor=True)
axes[1,
1].set_xticklabels(['$f_{1p}$', '$f_{2p}$', '$f_{3p}$', '$f_{4p}$'],
minor=True)
# labels
fig.text(0.05, 0.5, 'Magnitude [m]', va='center', rotation='vertical')
fig.text(0.5, 0.05, 'Frequency [Hz]', ha='center', rotation='horizontal')
#axes[1, 1].legend(loc='lower left')
axes[1, 1].legend()
if SAVE:
plt.savefig(SAVE, dpi=200, bbox_inches='tight')
plt.show()
print()
# print some results
fnp = 0.16 * np.array([1, 2, 3, 4])
for f in fnp:
pred = abs(signal.freqresp(system.S, f * 2 * np.pi)[1][0]) * 100 - 100
act = Ycl(f) / Yol(f) * 100 - 100
print('{:2.2f}%, {:2.2f}%'.format(pred, act))